Avinash Barnwal

Avinash Barnwal

Scientist with interests in Finance and Machine Learning

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Keeping Sight of Your Company’s Long-Term Vision

1 minute read

Published:

Problem

This is difficult enough, but even once a vision is in place, many leaders fail to execute it over the many years that it may require. They don’t translate the vision into a structured plan that they keep in focus over time. When change efforts require years, however, tracking often gets fuzzy, falling away in the face of rapidly changing business and economic conditions that force constant adaptation to produce day-to-day results.

books

No Rules Rules Netflix and Culture of Reinvention

Published:

Chapter - 1

A GREAT WORKPLACE IS STUNNING COLLEAGUES

  • Your number one goal as a leader is to develop a work environment consisting exclusively of stunning colleagues.
  • Stunning colleagues accomplish significant amounts of important work and are exceptionally creative and passionate.
  • Jerks, slackers, sweet people with nonstellar performance or pessimists left on the team will bring down the performance of everyone.

The Bezos Letters: 14 Principles to Grow Your Business Like Amazon

Published:

Test

  • Encourage “Successful Failure”—Blue Origin begins by experimenting small to see what works best (space exploration is a bit pricey, even for Bezos).
  • Bet on Big Ideas—Space travel is, obviously, a big idea.
  • Practice Dynamic Invention and Innovation—They have to invent and create for the unknowns in space travel.

How To Win Friends and Influence People

Published:

SIX WAYS TO MAKE PEOPLE LIKE YOU PRINCIPLE

  • Become genuinely interested in other people.
  • Smile.
  • Remember that a person’s name is to that person the sweetest and most important sound in any language.
  • Be a good listener. Encourage others to talk about themselves.
  • Talk in terms of the other person’s interests.
  • Make the other person feel important—and do it sincerely.

geeta

life

Cricket

Published:

Cricket

publications

Generalising the drift rate distribution for linear ballistic accumulators

Published in Journal of Mathematical Psychology Volumes 68–69, October–December 2015, Pages 49-58, 2015

The linear ballistic accumulator model is a theory of decision-making that has been used to analyse data from human and animal experiments.

Recommended citation: Andrew Terry and A.A.J. Marley and Avinash Barnwal and E.-J. Wagenmakers and Andrew Heathcote and Scott D. Brown (2015). "Generalising the drift rate distribution for linear ballistic accumulators." Journal of Mathematical Psychology . https://www.sciencedirect.com/science/article/abs/pii/S0022249615000577

Stacking with Neural Network for Cryptocurrency investment

Published in 2019 New York Scientific Data Summit (NYSDS), 2015

Predicting the direction of assets have been an active area of study and difficult task. Machine learning models have been used to build robust models to model the above task. Ensemble methods are one of them resulting better than single supervised method. We have used generative and discriminative classifiers to create the stack, particularly 3 generative and 6 discriminative classifiers and optimized over one-layer Neural Network to model the direction of price cryptocurrencies. Features used are technical indicators not limited to trend, momentum, volume, volatility indicators and sentiment indicators. For Cross validation, Purged Walk forward cross validation has been used. In terms of accuracy, we have done comparative analysis of the performance of Ensemble method with Stacking and individual models. We have also developed methodology for features importance for stacked model. Important indicators are identified based on feature importance.

Recommended citation: A. Barnwal, H. P. Bharti, A. Ali and V. Singh, &quot"Stacking with Neural Network for Cryptocurrency investment"&quot 2019 New York Scientific Data Summit (NYSDS) . https://ieeexplore.ieee.org/document/8909804

Network Elastic Net for Identifying Smoking specific gene expression for lung cancer

Published in 2019 New York Scientific Data Summit (NYSDS), 2019

Survival month for non-small lung cancer patients depend upon which stage of lung cancer is present. Our aim is to identify smoking specific gene expression biomarkers in prognosis of lung cancer patients. In this paper, we introduce the network elastic net, a generalization of network lasso that allows for simultaneous clustering and regression on graphs. In network elastic net, we consider similar patients based on smoking cigarettes per year to form the network. We then further find the suitable cluster among patients based on coefficients of genes having different survival month structures and showed the efficacy of the clusters using stage enrichment. This can be used to identify the stage of cancer using gene expression and smoking behavior of patients without doing any tests.

Recommended citation: A. Barnwal, "Network Elastic Net for Identifying Smoking specific gene expression for lung cancer," 2019 New York Scientific Data Summit (NYSDS), New York, NY, USA, 2019, pp. 1-4, doi: 10.1109/NYSDS.2019.8909802. https://ieeexplore.ieee.org/abstract/document/8909802

Survival regression with accelerated failure time model in XGBoost

Published in Arxiv, 2020

Survival month for non-small lung cancer patients depend upon which stage of lung cancer is present. Our aim is to identify smoking specific gene expression biomarkers in prognosis of lung cancer patients. In this paper, we introduce the network elastic net, a generalization of network lasso that allows for simultaneous clustering and regression on graphs. In network elastic net, we consider similar patients based on smoking cigarettes per year to form the network. We then further find the suitable cluster among patients based on coefficients of genes having different survival month structures and showed the efficacy of the clusters using stage enrichment. This can be used to identify the stage of cancer using gene expression and smoking behavior of patients without doing any tests.

Recommended citation: Barnwal, Avinash et al. “Survival regression with accelerated failure time model in XGBoost.” ArXiv abs/2006.04920 (2020): n. pag. https://arxiv.org/pdf/2006.04920.pdf

talks

teaching